The study explores the nature of convergence in affectivism versus cognitivism and its association with research impact. It uses affectivism, a research trend focusing on emotions' role in cognition and behavior, as a case study to investigate the generative mechanisms of convergence science. This contrasts with cognitivism, which traditionally neglects affect. The research is framed as a natural experiment examining the interplay between thematic diversity (multidisciplinarity) and research outcomes (measured by citation impact). A key question driving the research is whether convergence feeds upon itself, examining if a highly multidisciplinary paper leads to other highly multidisciplinary papers being published that cite it.

The paper traces the historical development of psychological research, starting with behaviorism's dominance in the first half of the 20th century. Behaviorism's limitations led to the rise of cognitivism in the 1950s, which focused on cognitive processes while largely neglecting affect. More recently, affectivism emerged to address the limitations of cognitivism by incorporating emotions and other affective processes. A recent consensus paper suggested affectivism as a rising, multidisciplinary trend, presenting it as a natural experiment in convergence science.

The study used PubMed as its bibliographic database, selecting publications based on psychologist-chosen MeSH terms for affective and cognitive topics. A total of 649,033 publications were analyzed, categorized as Affective, Cognitive, or Mixed (combining both affective and cognitive topics). Citation data were obtained from iCite. Thematic diversity (multidisciplinarity) was quantified for each publication and its citations using a combinatorial measure based on MeSH subject area terms (five categories: Biological Sciences, Psychological Sciences, Medical Sciences, Technical Methods, and Humanities). Citation impact was normalized using a log-normal transformation to account for temporal bias. Multiple linear regression and multinomial regression models were used to analyze the relationship between citation impact, publication type, and thematic diversity of publications and their citations. Control variables included author count and subject area keywords.

The study found that Affective publications had higher citation impact than Cognitive publications, and Mixed publications had the highest citation impact of all. Importantly, this higher impact for Affective and Mixed publications was strongly correlated with higher thematic diversity in their *citations*, indicating broader multidisciplinary appeal. However, there was a negative correlation between citation impact and thematic diversity *within* the publications themselves. This suggests that high impact is better associated with a multidisciplinary audience or appeal rather than multidisciplinary content. The model controlled for the number of authors and specific subject area content. Biological Sciences content showed a positive correlation with citation impact, while Medical Sciences, Technical Methods, and Humanities content showed negative correlations. A multinomial regression model further supported the finding that high multidisciplinary appeal, measured by the diversity of citing papers, is associated with Mixed publications.

The findings challenge the assumption that high internal thematic diversity leads to higher citation impact. The results suggest that the impact of a publication is more strongly determined by its appeal to a wider range of disciplines rather than the intrinsic multidisciplinarity of its content. The high impact of Mixed publications despite having relatively low internal multidisciplinarity supports this idea. The focused, yet broadly applicable nature of these publications may explain their success in attracting citations from diverse fields. Affective topics, for example, often have broader real-world relevance than specialized cognitive topics, leading to higher impact despite lower internal diversity. The paper demonstrates that convergence science's success might stem from generating highly valuable content that then attracts diverse fields, rather than merely starting with diverse content.

This study reveals that impactful research, particularly within the affectivism trend, is driven more by multidisciplinary appeal than by content multidisciplinarity. The high citation impact of Mixed publications, despite their limited internal thematic diversity, highlights the importance of generating broadly valuable concepts that attract citations across disciplines. Future research could further investigate the mechanisms underlying this phenomenon and explore whether similar patterns exist in other scientific fields. Investigating the specific factors that contribute to broad multidisciplinary appeal could prove especially valuable.

While the study utilizes a large dataset and robust statistical methods, some limitations exist. The reliance on PubMed data may not encompass all relevant publications across all disciplines. The use of MeSH terms for thematic analysis introduces a level of subjectivity, although the authors mitigated this by having experts select the terms and aggregating terms into larger subject areas. The study's correlational nature prevents definitive causal claims, although the results suggest a strong association between multidisciplinary appeal and research impact.